Intelligent production and processing control system for slicing and drying process of traditional Chinese medicinal materials

Abstract

The invention discloses an intelligent production and processing control system for a traditional Chinese medicinal material slicing and drying process, and relates to the technical field of production and processing control. According to the system, slice state data reflecting corresponding slice uniformity of traditional Chinese medicinal materials in a specified batch and drying state data reflecting drying uniformity are collected, and at least one processing mode of material state suitability analysis and processing state trend pre-judgment is adopted; material state data under the real-time regulation and control working condition are obtained, and the conveying speed of sliced materials is regulated and controlled in a self-adaptive mode synchronously based on the slicing load of current slicing equipment and the drying load of a drying cavity; according to the regulated and controlled conveying speed, the material state change condition is dynamically monitored, the suitability between the current material state and the corresponding slicing-drying cooperative control effect is quantified, and then the problems that in the prior art, the control process of the connection stage between traditional Chinese medicine slicing supply and drying treatment is lagged, and the efficiency is high are effectively solved. And the technical problem is solved.

Description

Technical Field

[0001] This invention relates to the field of production and processing control technology, and in particular to an intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials. Background Technology

[0002] Against the backdrop of the TCM industry's accelerated progress towards standardization, modernization, and internationalization, the TCM processing industry, as a core hub of the industrial chain, is developing rapidly at an average annual growth rate of 20%. Intelligentization, efficiency, and greening have become industry consensus. Slicing and drying, as key processes in TCM processing, directly determine the regularity of the medicinal materials' appearance, the retention rate of effective components, and storage stability. They are the core technological carriers for transforming raw materials into standardized products and an important guarantee for large-scale production. In actual processing, the slicing requirements for different TCM materials vary: those with whole petals (such as chrysanthemum and honeysuckle) and those with directional petal unfolding (such as rose) do not require conventional slicing. However, for the special needs of functional cut products, such as tea bags and compound granule raw material preparation, extremely thin slices (≤2mm) can be made. For those with petal removal (such as astragalus), the petals can be removed, and only the root and stem parts are processed. For those with petals involved in slicing (such as dendrobium) and multi-petaled TCM materials (such as chrysanthemum and roselle), customized slicing and drying processes are required based on the petal structure.

[0003] The current industry mainstream adopts a programmable logic controller (PLC) to build a collaborative control system to achieve process adaptation: the general slicing process uses an intelligent slicing system equipped with an intermittent feeding mechanism and flexible limit device, which can flexibly adjust parameters according to the texture of the medicinal material (e.g., the thickness of Dendrobium slices can be adjusted steplessly from 0.3-1.5mm); for chrysanthemum, a dedicated slicing system is optimized, which ensures quality through segmented feeding, flexible brush limit, servo drive (supporting stepless slicing from 0.5-2mm) and high-definition visual monitoring. After slicing, the slicing is connected to the drying process through an anti-compression flexible conveyor belt; the drying process is based on a heat pump system. The general process can accurately control the temperature and humidity field, while the customized solution for chrysanthemum is 40-50℃ constant temperature hot air, zoned air guidance, and intelligent dehumidification. The PLC will pre-store the process parameter library of different medicinal materials, collect data in real time through sensors, and dynamically adjust the slicing feeding speed, blade speed, drying heat pump power, and dehumidification frequency to achieve automated management.

[0004] However, as the processing industry of Chinese medicinal materials upgrades towards large-scale and refined production, the requirements for the adaptability of slicing and drying processes to working conditions and the consistency of materials continue to increase. In actual production, we often face the following challenges: the texture of Chinese medicinal materials from different producing areas (such as the hardness of roots and rhizomes, and the thickness of petals and fiber toughness of flowers and leaves) varies, which places higher demands on the adaptability of slicing cutting force and feeding rhythm; fluctuations in the initial moisture content of raw materials will directly affect the drying rate, requiring dynamic adjustment of temperature and humidity control logic.

[0005] When fluctuations occur in the processing environment and raw material condition, the monitoring components in the slicing stage primarily focus on the raw material position and blade status. This further leads to insufficient accuracy in identifying subtle differences in the texture of the medicinal herbs. The PLC struggles to adjust the cutting force and feeding rhythm accordingly, resulting in a deviation between the actual state of the material delivered to the drying stage and the controller's preset parameters, affecting drying uniformity. Secondly, while the sensors in the drying stage can monitor the surface moisture content of the material, they lack real-time sensing of the rate of moisture migration within the medicinal herb slices. The controller still relies mainly on preset programs to regulate equipment operation, making it unable to quickly respond to sudden situations such as fluctuations in the initial moisture content of the raw materials. This can easily lead to asynchrony between slice supply and drying processing.

[0006] The aforementioned problems do not necessarily occur in every batch of Chinese medicinal materials processing, but once they do, they will be directly reflected in the decrease in the uniformity of slice thickness, uneven color and retention rate of effective components after drying, etc. This causes the control process of the connection between the supply of Chinese medicinal material slices and the drying process to lag, resulting in an imbalance between the upstream and downstream processes, which in turn affects the standardized management and control of the entire process of Chinese medicinal material processing and the stability of product quality. Summary of the Invention

[0007] To address the technical problem of lagging control during the transition between the supply and drying of sliced ​​Chinese medicinal herbs in existing technologies, this invention provides an intelligent production and processing control system for the slicing and drying process of Chinese medicinal herbs. The technical solution is as follows: The material state perception and dynamic analysis module is used to collect slice state data reflecting the uniformity of sliced ​​Chinese medicinal materials in a specified batch, and drying state data reflecting the drying uniformity of the corresponding specified batch of Chinese medicinal materials. It adopts at least one processing method among material state adaptability analysis and processing state trend prediction. The slice-drying collaborative adaptation and control module is used to receive the execution results of the material state perception and dynamic analysis module, obtain material state data under real-time control conditions, and adaptively adjust the conveying speed of the material after slicing based on the current slicing load of the slicing equipment and the drying load of the drying chamber. The working condition fluctuation adaptive response module is used to dynamically monitor the changes in material state according to the adjusted conveying speed, and quantify the adaptability between the current material state and the corresponding slice-drying collaborative control effect.

[0008] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: 1. This invention solves the technical problem of imbalance between the supply and drying processes of Chinese medicinal materials due to lag in the control process during the connection stage, which is a problem in existing technologies. This is achieved by integrating three modules: material state perception and dynamic analysis, slicing-drying coordinated adaptation and control, and adaptive response to operating condition fluctuations. Specifically, the material state perception and dynamic analysis module collects data on slice uniformity and drying uniformity, performs state adaptability analysis and / or predicts processing state trends, effectively identifying subtle differences such as the hardness of root and rhizome materials, the thickness of petals and the toughness of fibers in flower and leaf materials, and the impact of raw material moisture content fluctuations on drying. The slicing-drying coordinated adaptation and control module receives the results of state adaptability analysis and / or processing state trend prediction, and adaptively adjusts the material conveying speed based on the load of the slicing equipment and the load of the drying chamber. This changes the passive control mode of PLC relying on preset parameters, achieving dynamic matching of cutting force, feeding rhythm, and drying rate. The adaptive response module dynamically monitors the material state after adjustment, quantifies the adaptability of coordinated control, and promptly corrects the problem of asynchronous slice supply and drying. The three modules work together to form a closed-loop management system, which effectively improves the consistency of slice thickness and drying uniformity, eliminates the lag in process connection, and ensures standardized management and control of the entire process of Chinese medicinal material processing and product quality stability.

[0009] 2. A comprehensive system for managing the entire process of slicing and drying Chinese medicinal herbs is constructed, comprising two main processes: material condition suitability analysis and processing trend prediction. The material condition suitability analysis process collects real-time physical state parameters such as slice flow rate, layer thickness uniformity, hot air penetration efficiency, and material conveying time. These parameters are compared with preset ranges, and the number of parameters exceeding the limits is counted to determine whether the material condition is acceptable. This allows for precise control of the slicing-drying process, preventing uneven drying caused by parameter exceeding limits. The processing trend prediction process plots the time-series changes in slice thickness and post-drying moisture content based on the monitoring period. By comparing these curves with historical curves from the same period, the period deviation rate and trend change rate are obtained. Four intervals are defined using -1, 0, and 1 as boundaries. The combination of these two indicators within these intervals determines trends such as stable optimization and gradual deterioration, providing timely warnings of changes in processing status. These two processes work together to effectively improve the perception accuracy of differences in the texture and moisture content of Chinese medicinal herbs, predict processing trends in advance, ensure consistent slice thickness and uniform drying, and provide data support for the intelligent and standardized processing of Chinese medicinal herbs.

[0010] 3. To address the adaptation requirements of the Chinese medicinal herb slicing-drying process, a scenario-based adaptive conveying speed control system is constructed. Differentiated control logic is formulated based on the different execution processes of the material state perception and dynamic analysis modules, effectively solving the problems of passive control and process adaptation imbalance. When performing material state adaptability analysis, physical state parameters, average material moisture content, and slicing-drying load deviation are used as core data. Single-case gradient adjustment and multi-case step-by-step control based on the priority of load deviation > physical state parameters > moisture content are employed to accurately match the conveying speed with process requirements. When performing processing state trend prediction, strategies such as maintaining speed, gradient speed reduction, speed reduction, or shortening the monitoring cycle are adopted based on the interval distribution of the periodic deviation rate and trend change rate to proactively avoid the risk of processing trend deterioration. When the two processes run in parallel, the basic control gradient is first determined by adaptability analysis, and then the trend prediction logic is superimposed to optimize the adjustment range, ensuring the accuracy and foresight of the control. The entire control system achieves dynamic adaptation under different material states and processing trends, effectively improving the collaborative efficiency of the slicing-drying process, ensuring the consistency of slice thickness and drying uniformity, reducing quality problems caused by material fluctuations and trend deterioration, and providing core support for the standardized and intelligent management of the entire process of Chinese medicinal material processing.

[0011] 4. Through multi-dimensional data collection and quantitative calculation, the compatibility between the material state and the slicing-drying coordinated control effect after conveyor speed adjustment is accurately determined, effectively ensuring the accuracy of control and the stability of process coordination. Specifically, in the first monitoring cycle after conveyor speed adjustment, physical state parameters, average material moisture content, and other material state data are collected simultaneously, as well as coordinated control effect data such as slice uniformity pass rate and drying moisture content compliance rate. By comparing preset intervals, the state compliance rate and effect compliance rate are calculated respectively, and the product of the two is used as the quantitative value of coordinated compatibility. Based on the comparison result of this quantitative value and preset threshold, it is determined whether the conveyor speed and material state match. If they match, the current speed is maintained; if they do not match, a compatibility deviation report is output. This process achieves accurate quantitative evaluation of compatibility, can promptly verify the control effect, detect compatibility deviations, avoid quality problems caused by improper control, and further strengthen the closed-loop control capability of the slicing-drying process. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A schematic diagram of the intelligent production and processing control system for slicing and drying Chinese medicinal materials provided in an embodiment of the present invention; Figure 2 A flowchart illustrating an intelligent production and processing control method for slicing and drying Chinese medicinal materials, provided in an embodiment of the present invention. Figure 3 A graph showing the relationship between the thickness and moisture content of Astragalus membranaceus slices provided in an embodiment of the present invention; Figure 4 A graph showing the relationship between the thickness of Dendrobium slices and the moisture content provided in an embodiment of the present invention. Detailed Implementation

[0014] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0015] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0016] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments. Example 1

[0017] This invention provides an intelligent production and processing control system for the slicing and drying of Chinese medicinal materials, such as... Figure 1 The diagram shown illustrates the structure of an intelligent production and processing control system for the slicing and drying of Chinese medicinal herbs. This system may include the following modules: The material state perception and dynamic analysis module is used to collect slice state data reflecting the uniformity of sliced ​​Chinese medicinal materials in a specified batch, and drying state data reflecting the drying uniformity of the corresponding specified batch of Chinese medicinal materials. It adopts at least one processing method among material state adaptability analysis and processing state trend prediction. The slice-drying collaborative adaptation and control module is used to receive the execution results of the material state perception and dynamic analysis module, obtain material state data under real-time control conditions, and adaptively adjust the conveying speed of the material after slicing based on the current slicing load of the slicing equipment and the drying load of the drying chamber. The working condition fluctuation adaptive response module is used to dynamically monitor the changes in material state according to the adjusted conveying speed, and quantify the adaptability between the current material state and the corresponding slice-drying collaborative control effect.

[0018] The material state perception and dynamic analysis module includes a multi-source data acquisition unit and a state intelligent analysis unit. The multi-source data acquisition unit acquires the slice thickness deviation and slice dispersion uniformity of a specified batch of Chinese medicinal materials during the slicing process, as well as the surface moisture content and material layer temperature difference within the drying chamber during the drying process. After data noise reduction and standardization calibration, a material state dataset reflecting the corresponding material state characteristics of the specified batch of Chinese medicinal materials during slicing and drying is obtained. This dataset integrates slice thickness deviation, slice dispersion uniformity, surface moisture content, and material layer temperature difference within the drying chamber, representing a standardized data set characterizing the material state of Chinese medicinal materials throughout the slicing-drying process. The state intelligent analysis unit performs material state adaptability analysis and / or processing state trend prediction based on the material state dataset. Material state adaptability analysis assesses the matching degree between the slice state of Chinese medicinal materials and the drying capacity of Chinese medicinal materials within the current monitoring period. Processing state trend prediction assesses the changing trends of slice uniformity and drying uniformity of Chinese medicinal materials within the next monitoring period.

[0019] Slice thickness deviation represents the absolute value of the difference between the average actual measured thickness of slices in a specified batch and the preset standard thickness. The actual measured thickness is obtained through a contact thickness gauge or a laser thickness sensor: multiple slice samples are randomly selected from the batch and measured one by one; the arithmetic mean of all sample measurements is the average actual measured thickness. Slice dispersion uniformity is the mean of the absolute values ​​of the deviations of the actual measured thickness of each individual slice from the average slice thickness of the batch in a specified batch of medicinal herbs; it is used to quantify the consistency level of slice thickness within the same batch. Material surface moisture content is the percentage of the average surface moisture mass of the slices in a specified batch of medicinal herbs during the drying process, characterizing the material's moisture content during the drying stage. The surface moisture state and average surface moisture mass are obtained using a near-infrared moisture meter: without damaging the sliced ​​sample, the surface of the sample is directly scanned and detected, and the surface moisture mass is output. The arithmetic mean of the surface moisture masses of all samples is the average surface moisture mass. The temperature difference of the material layer in the drying chamber refers to the average temperature deviation of the environment of different material carrier layers and different areas of the same carrier layer in the drying chamber of a specified batch of Chinese medicinal materials. It is obtained by synchronously collecting real-time temperature data at each location through multi-point distributed temperature sensors, calculating the absolute value of the deviation between the temperature of each collection point and the average temperature of the material layer in the chamber corresponding to all collection points, and then taking the average value. This can effectively quantify the uniformity of the temperature distribution in the drying environment.

[0020] The aforementioned collection points are set up by pre-designated personnel according to the principle of uniform distribution and comprehensive coverage. Specifically, collection points are set up at the center and four corners of different material support layers (upper, middle, and lower material racks), as well as at the front, middle, and rear areas along the material conveying direction of the same support layer. This ensures that the collection points can comprehensively capture temperature changes in different areas of the drying chamber, guaranteeing the representativeness and comprehensiveness of the temperature data collection.

[0021] Specifically, the material state adaptability analysis process is as follows: Physical state parameters of the slicing-drying connection process are collected during the current monitoring period, including the real-time flow rate of the slice conveyor, the uniformity of the slice layer thickness, and the hot air penetration efficiency and material conveying time of the drying equipment. The real-time flow rate of the slice conveyor is collected in real time by a weighing flow sensor installed at the discharge end of the slice conveyor belt, which collects the mass of medicinal herb slices passing through per unit time and obtains the data after calibration. The uniformity of layer thickness is obtained through a laser ranging sensor array, with sensors deployed at multiple cross-sections along the slice conveying path. The device synchronously collects the thickness of the slices at each point, and calculates the average absolute value of the deviation between the thickness of the slices at each point and the average thickness, which is the uniformity of the layer thickness. The hot air penetration efficiency is obtained by collecting the wind pressure difference between the upper and lower sides of the slice layer in the drying chamber through the wind pressure sensor, and converting it with the preset material permeability coefficient. The preset material permeability coefficient refers to the parameter that allows air to penetrate a slice layer of unit thickness, which is measured in the historical production and processing process for different types of Chinese medicinal materials. This parameter needs to be calibrated in advance according to the material of Chinese medicinal materials (such as roots and stems, flowers and leaves), slice thickness and moisture content.

[0022] The physical state parameters are compared one by one with their corresponding preset physical state parameter ranges. The number of parameters exceeding the preset range and its corresponding preset range is counted. The preset physical state parameter ranges are defined based on the processing standards of different types of Chinese medicinal materials, the rated operating parameters of the equipment, and historical qualified production data. The preset range is usually set at ±5%. When the type of Chinese medicinal material is changed, the processing batch is adjusted, or the equipment operating conditions change significantly, fine adjustments can be made based on the real-time collected basic process parameters (such as slicing rate and drying temperature). If the number of parameters is no more than 1, the material state at the slicing-drying junction is considered qualified because a small number of parameters... Slight deviations will not affect the coordinated matching of the slicing-drying process, and subsequent adjustments can quickly correct it. However, if the physical state parameter corresponding to the parameter number equal to 1 exceeds the preset safety threshold (the safety threshold is set to twice the preset range, i.e., ±10%), the material state corresponding to the slicing-drying junction is also deemed unqualified. If the parameter number is greater than 1, the material state corresponding to the slicing-drying junction is deemed unqualified because multiple parameters exceeding the preset range will cause a serious imbalance between the slice supply rate and the drying capacity, directly affecting the drying uniformity, material drying quality, and subsequent processing stability. The coordinated matching state cannot be quickly restored through simple adjustments.

[0023] When performing the material state adaptability analysis process, the conveying speed of the material after slicing is adaptively adjusted. Specifically, this includes: recording the absolute value of the difference between the slicing load and the drying load as the load deviation. The slicing load refers to the quality of Chinese medicinal material slices output by the slicing equipment per unit time, reflecting the material supply intensity of the slicing process; the drying load refers to the quality of Chinese medicinal material slices that the drying chamber can handle per unit time, reflecting the maximum carrying capacity of the drying process. The load deviation is used to quantify the matching degree between the supply rate of the slicing process and the processing capacity of the drying process. The smaller the value, the more balanced the load of the slicing-drying process. If the physical state parameters are all within the corresponding preset physical state parameter range, the average moisture content of the material is within the preset allowable range of material moisture content, and the load deviation is not greater than the preset load deviation, then the PLC is prompted to maintain the current conveying speed to ensure the coordinated matching of the slicing-drying process. The preset allowable range of material moisture content is determined according to the safe storage requirements and subsequent processing standards of different types of Chinese medicinal materials. For example, it is set to 8%-12% for root and rhizome Chinese medicinal materials and 6%-10% for flower and leaf Chinese medicinal materials. The preset load deviation is determined based on the rated processing capacity of the equipment to ensure that the process load is within a stable and adaptable range.

[0024] Scenario 1: If only a single physical state parameter is outside the corresponding preset physical state parameter range, the PLC will be prompted to adjust the corresponding gradient conveying speed based on the deviation of the corresponding physical state parameter. For example, if the single physical state parameter is the real-time flow rate of the slice conveying, and the flow rate exceeds the upper limit of the corresponding preset physical state parameter range (i.e., too many slices are being supplied), the PLC will be prompted to reduce the conveying speed of the gradient corresponding to the deviation from the upper limit to reduce the slice supply and bring the slice conveying flow rate back to the preset range, ensuring the load balance of the slice-drying process. If the flow rate is below the lower limit of the preset physical state parameter range (i.e., insufficient slice supply), the PLC will be prompted to increase the conveying speed of the gradient corresponding to the deviation from the lower limit to increase the slice supply, ensuring that the drying equipment operates at full load and efficiently, while avoiding waste of drying chamber resources.

[0025] Scenario 2: If only the average moisture content of the material is outside the preset allowable range, the PLC will be prompted to adjust the corresponding gradient of conveying speed based on the percentage of moisture content exceeding the limit. For example, if the average moisture content of the material is higher than the upper limit of the preset allowable range (such as 15% moisture content of root and rhizome Chinese medicinal materials), it means that the material needs a longer drying time, and the PLC will be prompted to reduce the conveying speed; if the moisture content is lower than the lower limit of the preset allowable range (such as only 5%), the PLC will be prompted to appropriately increase the conveying speed to avoid over-drying.

[0026] Scenario 3: If only the load deviation is greater than the preset load deviation, the PLC will be prompted to reduce the corresponding gradient conveying speed based on the deviation magnitude of the load deviation (i.e., the difference between the load deviation and the preset load deviation). In this case, the excessive load deviation means that the slice supply rate far exceeds the drying capacity. Reducing the conveying speed can quickly balance supply and demand and avoid insufficient drying.

[0027] If there are multiple scenarios, the priority order is 3 > 1 > 2. The core of this priority setting is to prioritize ensuring the balance of the slice-drying load, and then gradually optimize the material state adaptability to ensure the targeted and effective control. The specific execution process is as follows: First, based on the deviation data of the highest priority scenario, determine the basic adjustment gradient of the conveying speed. Then, based on the deviation data of the next lower priority scenario, fine-tune the basic adjustment gradient to obtain the basic adjustment gradient of the conveying speed after fine-tuning. If all three scenarios exist, after completing the first-level and second-level control, combine the deviation data of the lowest priority scenario to fine-tune the basic adjustment gradient of the conveying speed after fine-tuning again to determine the adjustment gradient corresponding to the final conveying speed, and prompt the PLC to adjust the conveying speed.

[0028] Quantifying the compatibility between the current material state and the corresponding slice-drying coordinated control effect specifically includes: within the first monitoring cycle after the conveyor speed is adjusted, simultaneously acquiring material state data and coordinated control effect data. Material state data includes physical state parameters and average material moisture content, while coordinated control effect data includes slice uniformity pass rate and drying moisture content compliance rate. Slice uniformity pass rate = number of slices with thickness within the preset standard range within the monitoring cycle / total number of slices sampled × 100%. Sampling must cover all monitoring nodes to ensure sample representativeness. Drying moisture content compliance rate = percentage of material batches with moisture content within the preset allowable range within the monitoring cycle / total number of monitored batches × 100%. Multiple samples are randomly selected from each batch for testing, and the average value is used for judgment.

[0029] The physical state parameters and the average moisture content of the material are compared with the corresponding preset physical state parameter ranges and the preset allowable range of material moisture content, respectively. For each physical state parameter, the number of monitoring nodes that are within the preset range during the monitoring period is counted, and the result is divided by the total number of monitoring nodes to obtain the compliance rate of the individual physical state parameter. The compliance rate of the average moisture content of the material is calculated based on the proportion of time during which the moisture content is within the allowable range during the monitoring period. The final compliance rate is the arithmetic mean of the compliance rates of all individual parameters.

[0030] The collaborative control effect data is compared with the corresponding preset process collaborative control standard range: if a certain collaborative control effect data (such as the slice uniformity pass rate) is within the preset standard range, the achievement rate of this effect is recorded as 100%; if it is lower than the lower limit of the range, it is calculated as actual value / lower limit of the range × 100%; if it is higher than the upper limit of the range (if the standard range is set as the upper limit threshold), it is still recorded as 100%; the final achievement rate is the arithmetic mean of the achievement rates of the two collaborative control effect data.

[0031] The product of the state compliance rate and the effect compliance rate is used as the quantification value of the synergistic adaptability to determine the adaptability of the current conveying speed. Specifically, if the obtained quantification value of synergistic adaptability is not less than the preset quantification value of synergistic adaptability, it is determined that the current conveying speed matches the material state, and the PLC is prompted to maintain the current conveying speed. The preset quantification value of synergistic adaptability is represented by the average of the summation of the historical quantification values ​​of synergistic adaptability under multiple qualified working conditions in the historical processing of the same type of Chinese medicinal materials. Otherwise, it is determined that the current conveying speed does not match the material state, and an adaptability deviation report is output based on the deviation of the quantification value of synergistic adaptability. The report includes the deviation value and the key parameters that caused the deviation, such as a certain physical state parameter not meeting the standard or the drying moisture content compliance rate being too low.

[0032] In Example 1, intelligent control of the entire process of slicing and drying Chinese medicinal materials was achieved through the coordinated operation of three major modules. The material state perception and dynamic analysis module accurately captures multi-dimensional material state data and, combined with adaptability analysis, achieves precise assessment of the current operating conditions. The slicing-drying collaborative adaptability control module dynamically optimizes the conveying speed based on a load balancing priority strategy, ensuring process adaptability. The operating condition fluctuation adaptive response module achieves closed-loop verification of the control effect through quantitative adaptability. This system effectively solves problems such as insufficient material fluctuation adaptability and process coordination imbalance in traditional processing, improves the uniformity of slicing and the stability of drying quality, reduces the cost of manual intervention, and provides reliable technical support for the large-scale and standardized production of Chinese medicinal materials.

[0033] Example 1 describes the material state adaptability analysis process, and the corresponding execution process for adaptively adjusting the conveying speed of the sliced ​​material. Similarly, a supplementary example, Example 2, is added based on Example 1. The specific process is as follows: Example 2

[0034] The specific process for predicting the processing status trend is as follows: Taking the current monitoring period (i.e., the preset fixed processing time period, such as 30 minutes) as the time dimension, each monitoring node is a sampling point set up at equal time intervals within the period (e.g., one node every 2 minutes); firstly, extract the data of the thickness of the Chinese medicinal material slices and the moisture content after drying corresponding to each monitoring node, and sort them according to the order of each monitoring node (i.e., the order of time flow); the horizontal axis is the time axis, marking the time corresponding to each monitoring node, and the vertical axis is the slice thickness (unit: mm) and the moisture content after drying (unit: %), respectively. Plot the two sets of data after sorting point by point according to the correspondence between time and value, and then connect each point with a smooth curve to obtain the time-series change curve corresponding to the slice uniformity and drying uniformity.

[0035] The time-series variation curve is compared with the corresponding time-series variation curve of the same period in history for each monitoring node: the absolute value of the difference between the current uniformity index data (slice thickness or moisture content after drying) of the same monitoring node and the uniformity index data of the corresponding node in the same period in history is divided by the uniformity index data of the corresponding node in the same period in history to obtain the period deviation rate of that node. The average of the period deviation rates of all nodes is the final period deviation rate. Similarly, the absolute value of the difference between the current uniformity index data of the same monitoring node and the uniformity index data of the corresponding node in the same period in history is divided by the average difference of adjacent nodes in the same period in history to obtain the single-group trend change rate. The average of the single-group trend change rates of all nodes is the final trend change rate.

[0036] The intervals excluding 0 are defined by the boundaries of -1, 0, and 1. These intervals are the first, second, third, and fourth intervals, with the corresponding values ​​increasing sequentially. Specifically, the first interval is the interval [-∞, -1], the second interval is the interval [-1, 0], the third interval is the interval [0, 1], and the fourth interval is the interval [1, +∞).

[0037] If both the period deviation rate and the trend change rate are in the second interval, the trend corresponding to the uniformity index is determined to be a stable optimization trend. This is because the value in this interval indicates that the current uniformity index is slightly better than the benchmark compared to the same period in history, and the trend is stable without drastic fluctuations. The current processing parameters are well adapted, so the current processing status should be maintained.

[0038] If both the period deviation rate and the trend change rate are in the third interval, the trend corresponding to the uniformity index is determined to be a gradual deterioration trend. This is because the value in this interval indicates that the current uniformity index deviates slightly from the benchmark compared to the same period in history and is in a deteriorating state. If not paid attention to in time, the deviation may be aggravated, and subsequent targeted adjustments are required.

[0039] If both the period deviation rate and the trend change rate are in the first interval, the trend corresponding to the uniformity index is determined to be a rapid optimization trend. This is because the value in this interval represents that the current uniformity index is significantly better than the benchmark compared to the same period in history, and the optimization rate is fast. The processing status is in a high-quality and stable state, so the current processing status is maintained.

[0040] If both the period deviation rate and the trend change rate are in the fourth interval, the trend corresponding to the uniformity index is determined to be a rapid deterioration trend. This is because the value in this interval indicates that the current uniformity index deviates significantly from the benchmark compared to the same period in history, and the deterioration speed is fast. If intervention is not timely, it will seriously affect the product quality.

[0041] If both the period deviation rate and the trend change rate are equal to 0, then the trend corresponding to the uniformity index is determined to be a stable trend without fluctuations. The reason is that the two indicators being 0 indicates that the uniformity index of each monitoring node is completely consistent with the historical period, and there is no change between adjacent nodes. The processing status is extremely stable, so the current processing status is maintained.

[0042] In addition to the above situations, the trend corresponding to the uniformity index is determined to be a fluctuating trend with no significant tendency. This is because the period deviation rate and the trend change rate belong to different intervals, and the index change pattern is chaotic, making it impossible to clearly determine whether it is an optimization or deterioration trend. The preset amplitude here refers to the pre-set proportion of shortening the monitoring period (e.g., shortening it by 30%). Shortening the monitoring period here is to collect data more intensively, accurately capture subsequent state changes, and promptly discover potential optimization or deterioration trends, avoiding the expansion of deviation due to excessively long monitoring intervals.

[0043] When executing the processing status trend prediction process, the conveying speed of the material after slicing is adaptively adjusted. Specifically, if the material status data are all in the first interval, the second interval, or all equal to 0, the PLC is prompted to maintain the current conveying speed. This is because these three situations indicate that the processing status is in an optimized or stable state, the current process parameters are well adapted, and no adjustment is needed to ensure the uniformity of slicing and drying. If the material status data are all in the third interval, the PLC is prompted to reduce the conveying speed according to the gradient corresponding to the superposition amplitude of the material status data. This is because the gradual deterioration trend will exacerbate the deviation if left unchecked. Reducing the conveying speed can slow down the material processing rhythm and allow time for process adaptation adjustments. Here, the superposition amplitude is determined by the weekly... The absolute values ​​of the period deviation rate and the trend change rate are added together. The larger the superposition amplitude, the more obvious the deterioration, and the higher the corresponding adjustment gradient. If the material status data are all in the fourth interval, the PLC is prompted to reduce the conveying speed according to the gradient corresponding to the superposition amplitude, based on the superposition amplitude of the period deviation rate and the trend change rate. If the material status data belong to different intervals, it is because the parameter change pattern is chaotic at this time, and it is impossible to clearly determine whether it is an optimization or deterioration trend, making it difficult to formulate a precise adjustment strategy. In this case, the PLC is prompted to maintain the current conveying speed while shortening the monitoring cycle of the preset amplitude. Shortening the monitoring cycle is to collect data more intensively, capture subsequent status changes in real time, discover potential trends in time, and avoid the deviation from expanding due to excessively long monitoring intervals.

[0044] In Example 2, the deviation rate calculation method by comparing time-series curves with historical data improves the objectivity and accuracy of trend judgment and avoids subjective experience-based misjudgments. The trend classification through multi-interval subdivision can accurately distinguish the state of different optimization / deterioration levels, providing a basis for differentiated regulation. Through the speed regulation strategy and the dynamic adjustment mechanism of the monitoring cycle, it can maintain efficient production when the state is stable, and can intervene in deterioration trends in advance and accurately capture fluctuations, providing strong support for the stability and standardization of Chinese medicinal material processing.

[0045] Example 2 describes the process for predicting the processing status trend, and the corresponding execution process for adaptively adjusting the conveying speed of the sliced ​​material after the process. Similarly, based on Example 1 and Example 2, a supplementary example is added, namely Example 3, and the specific process is as follows: Example 3

[0046] When executing the material state adaptability analysis and processing state trend prediction process, the conveying speed of the sliced ​​material is adaptively adjusted. Specifically, this includes: first, executing the control logic of the material state adaptability analysis, combining the load deviation range, the deviation range of physical state parameters, and the proportion of material moisture exceeding the standard, and determining the dominant control factor according to the principle of load balance priority (case 3 > case 1 > case 2), thereby determining the basic control gradient of the conveying speed to ensure that the core adaptability requirements of the process are met first; then, superimposing the control logic of the processing state trend prediction. If the cycle deviation rate and the trend change rate both belong to the optimization or deterioration range, the adjustment range is increased by a preset proportion on the basic control gradient to strengthen the trend guidance effect; if the two belong to different ranges, it indicates that the state change pattern is chaotic and the trend control cannot be accurately superimposed. At this time, the conveying speed is adjusted according to the basic control gradient, while the monitoring cycle of the preset range is shortened to collect data intensively to capture subsequent state changes, ensuring the safety and pertinence of the control.

[0047] In Example 3, the fusion of dual-process logic enables coordinated control of real-time working condition adaptation and future trend prediction. This not only ensures the balance of the current process but also avoids trend deviations in advance, further improving the accuracy and foresight of conveying speed control and adapting to the complex and ever-changing working conditions of Chinese herbal medicine processing.

[0048] In summary, as Figure 2 The flowchart shown illustrates an intelligent production and processing control method for the slicing and drying processes of traditional Chinese medicinal materials. Taking the large-scale processing of Astragalus membranaceus (Huangqi), a root and rhizome-type traditional Chinese medicinal material, as an example, the intelligent production and processing control system of this invention can achieve efficient and precise coordinated management and control of slicing and drying. The uniformity of Astragalus membranaceus slice thickness and the drying moisture content directly affect the retention of its medicinal components. However, in actual processing, differences in the size of Astragalus membranaceus raw materials and fluctuations in batch moisture content can easily lead to imbalances in operating conditions. Therefore, adopting at least one of the following approaches—material state adaptability analysis and processing state trend prediction—is fully reasonable: single adaptability analysis can solve the problem of immediate operating condition imbalance, while single trend prediction can avoid trend-based quality risks in advance. The combination of the two can achieve dual protection of immediate control and forward-looking prediction, adapting to complex and ever-changing processing scenarios.

[0049] In specific scenarios, if fluctuations in the slice conveying flow occur during the initial stage of Astragalus processing, the system, through the material state adaptability analysis in Example 1, adjusts the conveying speed according to the principle of load balancing to quickly balance the slice and drying loads. If the drying uniformity time-series curve shows a gradual deterioration trend during the middle of processing, the trend prediction process in Example 2 can be activated to reduce the conveying speed in advance and mitigate the deterioration. In complex situations such as raw material batch switching, the dual-process fusion control in Example 3 can take into account both real-time adaptability and trend guidance. Through multiple examples covering different processing needs, this system effectively improves the uniformity of Astragalus slices and the stability of drying quality, providing reliable technical support for the standardized production of Chinese medicinal materials.

[0050] It should be added that, such as Figure 3 The graph showing the relationship between Astragalus membranaceus slice thickness and moisture content includes three sub-graphs, corresponding to slice thicknesses of 2.6 mm, 2.4 mm, and 2.2 mm, respectively. The monitoring nodes for each sub-graph are sampling points set up every 2 minutes within the monitoring period. The horizontal axis of each sub-graph represents the initial moisture content (%) of Astragalus membranaceus, showing the change in moisture content at different time points under different initial moisture contents: as time progresses, i.e., as the drying process continues, the moisture content of slices of all thicknesses decreases. The red dashed line in the graph represents the critical line for achieving the moisture content standard (corresponding to the upper limit of the moisture content allowed by the process). The moisture content at the nodes to the right of the dashed line generally exceeds the standard range. This graph can guide production: if the initial moisture content of Astragalus membranaceus is high, it is recommended to use 2.2 mm thin slices. Additionally, drying parameters can be adjusted earlier in the monitoring period (lower sequence nodes) to avoid exceeding the moisture content standard later.

[0051] like Figure 4 The graph showing the relationship between Dendrobium slice thickness and moisture content also includes three sub-graphs, corresponding to slice thicknesses of 1.4mm, 1.2mm, and 1.0mm (extremely thin slices). The monitoring nodes for each sub-graph are sampling points placed at equal time intervals (e.g., every 2 minutes) within the cycle, corresponding to the time progress within the cycle. The horizontal axis of each sub-graph represents the initial moisture content (%) of the Dendrobium. The curves show the change in Dendrobium moisture content at different time points under different initial moisture contents: as time progresses, i.e., as the drying process continues, the moisture content of slices of all thicknesses decreases. The red dashed line in the graph represents the critical line for achieving the moisture content standard, indicating the upper limit standard for the moisture content of Dendrobium after drying. The moisture content at the node to the right of the dashed line has exceeded the allowable range of the process. This graph can guide production: if the initial moisture content of Dendrobium is high, it is recommended to use 1.0mm ultra-thin slices and adjust the drying parameters in the early stages of the monitoring cycle (lower number nodes) to avoid exceeding the moisture content standard later.

[0052] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0053] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0054] In various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0055] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0056] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials, characterized in that, The system includes: The material state perception and dynamic analysis module is used to collect slice state data reflecting the uniformity of slices of Chinese medicinal materials in a specified batch, and drying state data reflecting the drying uniformity of the corresponding specified batch of Chinese medicinal materials, and adopt at least one of the following processing methods: material state adaptability analysis and processing state trend prediction. The slicing-drying collaborative adaptation and control module is used to receive the execution results of the material state perception and dynamic analysis module, obtain material state data under real-time control conditions, and adaptively control the conveying speed of the material after slicing based on the current slicing load of the slicing equipment and the drying load of the drying chamber. The adaptive response module for operating condition fluctuations is used to dynamically monitor changes in the material state based on the adjusted conveying speed, and to quantify the adaptability between the current material state and the corresponding slice-drying collaborative control effect.

2. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 1, characterized in that, The material state perception and dynamic analysis module includes a multi-source data acquisition unit and a state intelligent analysis unit; The multi-source data acquisition unit is used to acquire the slice thickness deviation and slice dispersion uniformity of a specified batch of Chinese medicinal materials during the slicing process, as well as the surface moisture content and material layer temperature difference of a specified batch of Chinese medicinal materials during the drying process. After data noise reduction and standardization calibration, a material state dataset is obtained. The intelligent state analysis unit is used to perform material state adaptability analysis and / or processing state trend prediction based on the material state dataset. The slice thickness deviation represents the absolute value of the difference between the average actual measured thickness of slices of Chinese medicinal materials in a specified batch and the preset standard thickness; The uniformity of slice dispersion represents the average absolute value of the deviation of the actual measured thickness of each individual slice from the average thickness of the batch of slices in a specified batch of Chinese medicinal materials. The surface moisture content of the material represents the percentage of the average surface moisture mass of a specified batch of Chinese medicinal herb slices during the drying process to the total mass of the slices. The temperature difference of the material layer in the drying chamber represents the average temperature deviation of the environment in which the sliced ​​Chinese medicinal materials of a specified batch are located in different material carrier layers and different areas of the same carrier layer within the drying chamber.

3. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 2, characterized in that, The specific process of the material state adaptability analysis is as follows: Collect physical state parameters of the slicing-drying process during the current monitoring period, including the real-time flow rate of the slice conveyor, the uniformity of the slice layer thickness, and the hot air penetration efficiency and material conveying time of the drying equipment. The physical state parameters are compared one by one with the corresponding preset physical state parameter ranges, and the number of parameters that exceed the preset amplitude of the corresponding preset physical state parameter range is counted. If the number of parameters is not greater than 1, the material state at the junction of slicing and drying is deemed to be qualified; otherwise, the material state at the junction of slicing and drying is deemed to be unqualified.

4. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 2, characterized in that, The specific process for predicting the processing status trend is as follows: Using the current monitoring period as the time dimension, the thickness of the Chinese medicinal material slices and the moisture content after drying monitored at each monitoring node within the current monitoring period are arranged one by one in the time sequence of each monitoring node, and the time-series change curves corresponding to slice uniformity and drying uniformity are plotted respectively. The time series variation curve is compared with the time series variation curve corresponding to the same period in history for each monitoring node to obtain the period deviation rate and trend change rate of each uniformity index. The intervals excluding 0 are defined with -1, 0 and 1 as boundaries, including the first interval, the second interval, the third interval and the fourth interval with the corresponding values ​​increasing. If both the period deviation rate and the trend change rate are in the first interval, then the trend corresponding to the uniformity index is determined to be a rapid optimization trend, and the current processing state is maintained. If both the period deviation rate and the trend change rate are in the second interval, then the trend corresponding to the uniformity index is determined to be a stable optimization trend, and the current processing state is maintained. If both the period deviation rate and the trend change rate are in the third interval, then the trend corresponding to the uniformity index is determined to be a gradual deterioration trend. If both the period deviation rate and the trend change rate are in the fourth interval, then the trend corresponding to the uniformity index is determined to be a rapid deterioration trend. If both the period deviation rate and the trend change rate are equal to 0, then the trend corresponding to the uniformity index is determined to be a stable trend without fluctuations, and the current processing state is maintained. In addition to the above situations, the trend corresponding to the uniformity index is determined to be a trend of fluctuation without significant tendency. The current processing status is temporarily maintained and the monitoring period of the preset amplitude is shortened.

5. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 2, characterized in that, When the material state perception and dynamic analysis module executes the material state adaptability analysis process, the material state data includes physical state parameters and average moisture content of the material. The adaptive adjustment of the conveying speed of the material after slicing specifically includes: The absolute value of the difference between the slicing load and the drying load is denoted as the load deviation; If all physical state parameters are within the corresponding preset physical state parameter range, the average moisture content of the material is within the preset allowable range of material moisture content, and the load deviation is not greater than the preset load deviation, then the PLC will be prompted to maintain the current conveying speed. If there is only a single physical state parameter that is not within the corresponding preset physical state parameter range, the PLC will be prompted to adjust the corresponding gradient conveying speed based on the deviation of the corresponding physical state parameter. If the average moisture content of the material is outside the preset allowable range, the PLC will be prompted to adjust the corresponding gradient conveying speed based on the proportion of the material moisture content exceeding the limit. If only the load deviation is greater than the preset load deviation, the PLC will be prompted to adjust the corresponding gradient conveying speed based on the deviation magnitude of the load deviation. If there are multiple cases, they will be executed in the order of their respective priorities.

6. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 5, characterized in that, The execution is carried out in the corresponding priority order, as follows: First, based on the deviation data of the highest priority case, determine the basic adjustment gradient of the conveying speed. Then, based on the deviation data of the second priority case, fine-tune the basic adjustment gradient to obtain the basic adjustment gradient of the corresponding conveying speed after fine-tuning. If all three conditions exist, after completing the first-level and second-level control, the basic adjustment gradient of the corresponding conveying speed after fine-tuning is fine-tuned again based on the deviation data of the lowest priority condition, to determine the adjustment gradient corresponding to the final conveying speed, and prompt the PLC to adjust the conveying speed.

7. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 2, characterized in that, When the material status perception and dynamic analysis module executes the processing status trend prediction process, the material status data includes the periodic deviation rate and the trend change rate. The adaptive adjustment of the conveying speed of the material after slicing specifically includes: If all material status data are in the first range, the PLC will be prompted to maintain the current conveying speed. If all material status data are in the second range, the PLC will be prompted to maintain the current conveying speed. If all material status data are in the third interval, then based on the corresponding superposition range, the PLC is prompted to reduce the conveying speed according to the gradient corresponding to the superposition range. If all material status data are in the fourth interval, then based on the corresponding superposition range, the PLC is prompted to reduce the conveying speed according to the gradient corresponding to the superposition range. If all material status data are equal to 0, the PLC will be prompted to maintain the current conveying speed. If the material status data belongs to different ranges, the PLC will be prompted to maintain the current conveying speed while shortening the monitoring cycle of the preset range.

8. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 2, characterized in that, When the material state perception and dynamic analysis module executes the material state adaptability analysis and processing state trend prediction process, the material state data includes physical state parameters, average material moisture content, periodic deviation rate and trend change rate. The adaptive adjustment of the conveying speed of the material after slicing specifically includes: First, the control logic of material state adaptability analysis is executed. Based on the load deviation range, the deviation range of physical state parameters, and the proportion of material moisture content exceeding the standard, the basic control gradient of the conveying speed is determined. Furthermore, the control logic based on the prediction of processing status trends is superimposed, and the adjustment range is increased on the basic control gradient. If the cycle deviation rate and the trend change rate belong to different ranges, the conveying speed is adjusted according to the basic control gradient, while the monitoring cycle of the preset range is shortened.

9. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 1, characterized in that, The quantification of the compatibility between the current material state and the corresponding slice-drying coordinated control effect specifically includes: During the first monitoring cycle after the conveying speed is adjusted, material status data and collaborative control effect data are acquired simultaneously. The material status data includes physical state parameters and average material moisture content. The collaborative control effect data includes slice uniformity pass rate and drying moisture content compliance rate. The physical state parameters and the average moisture content of the material are compared with the corresponding preset physical state parameter ranges and the preset allowable range of material moisture content, respectively, and the compliance rate of each parameter is calculated. The collaborative control effect data is compared with the corresponding preset process collaborative control standard range, and the achievement rate of each parameter is calculated. The product of the status compliance rate and the effect compliance rate is used as the quantitative value of collaborative adaptability to determine the adaptability of the current conveying speed.

10. The intelligent production and processing control system for the slicing and drying process of Chinese medicinal materials as described in claim 9, characterized in that, The adaptation determination for the current conveying speed specifically involves: If the quantified value of the cooperative adaptability is not less than the preset quantified value of the cooperative adaptability, it is determined that the current conveying speed matches the material state, and the PLC is prompted to maintain the current conveying speed. Conversely, if the current conveying speed does not match the material state, a mismatch is determined, and a mismatch deviation report is output based on the deviation of the quantified value of the compatibility.

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